Análisis estocástico de un sistema génico simple para la śintesis de una protéina implementando los métodos de Gillespie

Translated title of the contribution: Stochastic analysis of a simple gene system for protein synthesis implementing Gillespie's methods

Diana Carolina Clavijo Buritica, Barbara Valeria Mejia, Lina Maria Rojas, Leandro Saenz Castro

Research output: Contribution to journalArticlepeer-review

Abstract

In most cases where a biological network needs to be described, a system of coupled differential equations is proposed, which is then solved by numerical methods. However, when a single steady-state value does not predict the behavior of the total population, it is essential that the representation model describes the distribution of states within a system. The algorithm proposed by Gillespie in 1998 consists of the description of a specific phenomenon using stochastic tools, where the behavior of the master probability equation is predicted by Monte Carlo simulation. The author proposes two mathematical approaches for the resolution: the first reaction method and the direct method. The purpose of this research was to compare the results of these approaches using a simple gene model for the synthesis of a protein, represented in a simple Petri net proposed by Goss and Peccoud in 1998 (1), focusing on the differences between the results when analyzing the net by means of a classical deterministic method and the two stochastic methods of Gillespie. Finally, to perform a sensitivity analysis of the stochastic model with the null hypothesis test. The results obtained show that the population does not behave uniformly, so it is pertinent and advisable to use Gillespie's method for this system and for similar systems.
Translated title of the contributionStochastic analysis of a simple gene system for protein synthesis implementing Gillespie's methods
Original languageUndefined/Unknown
Pages (from-to)7-16
Number of pages9
JournalRevista Cuarzo
DOIs
StatePublished - Aug 2018

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